{
  "id": "decomposed-prompting",
  "code": "PTL-0114",
  "term": "Decomposed Prompting",
  "aliases": [
    "DecomP",
    "modular prompting"
  ],
  "category": "reasoning",
  "definition": "Decomposed prompting breaks a complex task into simpler sub-tasks, each delegated to its own prompt, model call, or symbolic function, with a controller prompt that decides which handler to call next.",
  "description": "Each sub-task handler can be optimized, given its own examples, or replaced with code, and handlers can call further decompositions recursively. Compared with a single chain-of-thought prompt, this modularity helps on tasks with steps that models do poorly in one pass, such as long-input processing or symbolic manipulation.",
  "example": null,
  "broader": [],
  "narrower": [],
  "related": [
    "least-to-most-prompting",
    "prompt-chaining",
    "orchestrator-workers",
    "program-aided-language-models"
  ],
  "introduced": 2022,
  "added": "2026-10-10",
  "sources": [
    {
      "title": "Decomposed Prompting: A Modular Approach for Solving Complex Tasks",
      "authors": "Khot et al.",
      "year": 2022,
      "url": "https://arxiv.org/abs/2210.02406"
    }
  ],
  "url": "https://protologue.com/t/decomposed-prompting/",
  "citation": "Protologue. (2026). Decomposed Prompting. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.4.0, PTL-0114). https://protologue.com/t/decomposed-prompting/"
}